Subhashini Venugopalan
Research Scientist

I am an ML/Vision researcher at Google working on problems in the intersection of biology, medicine, and machine learning. Prior to this, I was a PhD student at UT Austin working on natural language processing, and computer vision. I was a member of the Machine Learning Group, and was advised by Prof. Ray Mooney.

During my PhD I was also fortunate to work with Prof. Trevor Darrell's group at UC Berkeley and with Prof. Kate Saenko at Boston University. I spent several summers working on deep learning projects at Google Research (host: Varun Gulshan) and Google Brain (host: Andrea Frome). Prior to joining UT, I spent a year at IBM Research, India (Blue scholar).

In 2011, I obtained a Masters degree in Computer Science and Engineering from IIT, Madras. My thesis was advised by Prof. C. Pandu Rangan. In 2009, I graduated with a bachelor's degree in Information Technology from NITK, Surathkal.


Research

I enjoy applying machine learning to data of all modalities, and have worked with images, videos, text, audio, speech, and accelerometer. Some of my work pertains to transfer learning for bio/medical data (e.g. detecting diabetic retinopathy, breast cancer), and I have also developed methods to interpret such vision/audio models (XAI, model explanation) for medical applications. I have also applied natural language processing and computer vision techniques to generate descriptions of events depicted in videos and images. Please refer to my Google Scholar page for an up-to-date list of my publications.


Medical applications, XAI


Scientific Discovery by Generating Counterfactuals using Image Translation
Arunachalam Narayanaswamy*, Subhashini Venugopalan*, Dale R. Webster, Lily Peng, Greg Corrado, Paisan Ruamviboonsuk, Pinal Bavishi, Rory Sayres, Abigail Huang, Siva Balasubramanian, Michael Brenner, Philip Nelson, Avinash V. Varadarajan
*equal contribution

International Conference on Medical Image Computing and Computer Assisted Intervention (Lima, Peru) Virtual, October 2020. (MICCAI 2020)
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Attribution in Scale and Space
Shawn Xu, Subhashini Venugopalan, Mukund Sundararajan

IEEE Conference on Computer Vision and Pattern Recognition, (Seattle, USA) Virtual June 2020. (CVPR 2020)
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Scaling Symbolic Methods using Gradients for Neural Model Explanation
Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley

ArXiV, June 2020
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Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning
Avinash V Varadarajan, Pinal Bavishi, Paisan Ruamviboonsuk, Peranut Chotcomwongse, Subhashini Venugopalan, Arunachalam Narayanaswamy, Jorge Cuadros, Kuniyoshi Kanai, George Bresnick, Mongkol Tadarati, Sukhum Silpa-Archa, Jirawut Limwattanayingyong, Variya Nganthavee, Joseph R Ledsam, Pearse A Keane, Greg S Corrado, Lily Peng, Dale R Webster

Nature Communications, 2020.
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Detection of anaemia from retinal fundus images via deep learning
Akinori Mitani, Abigail Huang, Subhashini Venugopalan, Greg S Corrado, Lily Peng, Dale R Webster, Naama Hammel, Yun Liu, Avinash V Varadarajan

Nature BioMedical Engineering, 2019.
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Batch Equalization with a Generative Adversarial Network
Wesley Wei Qian, Cassandra Xia, Subhashini Venugopalan, Arunachalam Narayanaswamy, Jian Peng, D Michael Ando

European Conference on Computational Biology (ECCB) 2020.
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It's easy to fool yourself: Case studies on identifying bias and confounding in bio-medical datasets
Subhashini Venugopalan*, Arunachalam Narayanaswamy*, Samuel Yang*, Anton Gerashcenko, Scott Lipnick, Nina Makhortova, James Hawrot, Christine Marques, Joao Pereira, Michael Brenner, Lee Rubin, Brian Wainger, Marc Berndl
*equal contribution

NeurIPS Learning Meaningful Representations of Life (LMRL) Workshop, 2019.
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Applying Deep Neural Network Analysis to High-Content Image-Based Assays
Samuel J Yang*, Scott L Lipnick*, Nina R Makhortova*, Subhashini Venugopalan*, Minjie Fan*, Zan Armstrong, Thorsten M Schlaeger, Liyong Deng, Wendy K Chung, Liadan O’Callaghan, Anton Geraschenko, Dosh Whye, Marc Berndl, Jon Hazard, Brian Williams, Arunachalam Narayanaswamy, D Michael Ando, Philip Nelson, Lee L Rubin
*equal contribution

SLAS DISCOVERY: Advancing Life Sciences R&D, 2019
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Detecting cancer metastases on gigapixel pathology images
Yun Liu, Krishna Gadepalli, Mohammad Norouzi, George E Dahl, Timo Kohlberger, Aleksey Boyko, Subhashini Venugopalan, Aleksei Timofeev, Philip Q Nelson, Greg S Corrado, Jason D Hipp, Lily Peng, Martin C Stumpe

ArXiv, 2017
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Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
Varun Gulshan, Lily Peng, Marc Coram, Martin C Stumpe, Derek Wu, Arunachalam Narayanaswamy, Subhashini Venugopalan, Kasumi Widner, Tom Madams, Jorge Cuadros, Ramasamy Kim, Rajiv Raman, Philip C Nelson, Jessica L Mega, Dale R Webster

The Journal of the American Medical Association (JAMA), 2016.
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  • [Best of the Decade]

Vision and Language


Captioning Images with Diverse Objects
Subhashini Venugopalan, Lisa Hendricks, Marcus Rohrbach, Raymond Mooney, Kate Saenko, Trevor Darrell

IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, Hawaii, July 2017. (CVPR 2017)
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Semantic Text Summarization of Long Videos
Shagan Sah, Sourabh Kulhare, Allison Gray, Subhashini Venugopalan, Emily Prud'hommeaux, Raymond Ptucha

IEEE Winter Conference on Applications of Computer Vision Santa Rosa, California, March 2017. (WACV 2017)
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Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text
Subhashini Venugopalan, Lisa Hendricks, Raymond Mooney, Kate Saenko

Conference on Empirical Methods in Natural Language Processing, Austin, Texas, November 2016. (EMNLP 2016)
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Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data
Lisa Hendricks, Subhashini Venugopalan, Marcus Rohrbach, Raymond Mooney, Kate Saenko, Trevor Darrell

IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, Nevada, June 2016. (CVPR 2016)
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Sequence to Sequence - Video to Text
Subhashini Venugopalan, Marcus Rohrbach, Jeff Donahue, Raymond Mooney, Trevor Darrell, Kate Saenko

International Conference on Computer Vision, Santiago, Chile, December 2015. (ICCV 2015)
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Translating Videos to Natural Language Using Deep Recurrent Neural Networks
Subhashini Venugopalan, Huijun Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney, Kate Saenko

North American Chapter of the Association for Computational Linguistics, Denver, Colorado, June 2015. (NAACL-HLT 2015)
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Long-term Recurrent Convolutional Networks for Visual Recognition and Description
Jeff Donahue, Lisa Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, Trevor Darrell

IEEE Conference on Computer Vision and Pattern Recognition, Boston, Massachusetts, June 2015. (CVPR 2015)
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Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild
Jesse Thomason*, Subhashini Venugopalan*, Sergio Guadarrama, Kate Saenko, Raymond Mooney
*equal contribution

International Conference on Computational Linguistics, Dublin, Ireland, August 2014.(COLING 2014)
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YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-shot Recognition
Sergio Guadarrama,Niveda Krishnamoorthy, Girish Malkarnenkar, Subhashini Venugopalan, Raymond Mooney, Trevor Darrell, Kate Saenko

International Conference on Computer Vision, Sydney, Australia, December 2013.(ICCV 2013)
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Other Research

In the past I have researched on topics in public policy, theoretical cryptography and social network analysis.


Topic based classification and pattern identification in patents
Subhashini Venugopalan, Varun Rai

Technological Forecasting and Social Change, 2014
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People and Entity Retrieval in Implicit Social Networks
Suman K. Pathapati, Subhashini Venugopalan, Ashok P. Kumar, Anuradha Bhamidipaty

IEEE International Conference on Internet Multimedia Systems Architecture and Application, Bangalore, India December 2011. (IMSAA 2011)
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A New Approach to Threshold Attribute Based Signatures
S. Sharmila Deva Selvi, Subhashini Venugopalan, C Pandu Rangan

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Contact


github.com/vsubhashini